High-Efficiency Methane Production via Electrochemical CO2 Reduction in Aqueous Bicarbonate Systems
Bibliographic record
Abstract
High-Efficiency Methane Production via Electrochemical CO2 Reduction in Aqueous Bicarbonate SystemsViktoria Golovanova a, Cornelius Obasanjo b, Guorui Gao b, Jackson Crane b, F. Pelayo García de Arquer a, Cao-Thang Dinh ba ICFO - Institut de Ciències Fotòniques, The Barcelona Institute of Science and Technology, 08860, Castelldefels, Spainb Department of Chemical Engineering, Queen's University, Kingston, ON K7L 3N6, CanadaMaterials for Sustainable Development Conference (MATSUS)Proceedings of MATSUS Spring 2024 Conference (MATSUS24)#MatInter - Materials and Interfaces for emerging electrocatalytic reactionsBarcelona, Spain, 2024 March 4th - 8thOrganizers: Marta Costa Figueiredo and María Escudero-EscribanoOral, Viktoria Golovanova, presentation 227DOI: https://doi.org/10.29363/nanoge.matsus.2024.227Publication date: 18th December 2023The urgent need for large-scale renewable energy storage and carbon mitigation strategies calls for efficient methods of converting carbon dioxide (CO2) into valuable hydrocarbon fuels1. Among these, methane (CH4) holds particular promise due to its high energy density and compatibility with existing infrastructure. Electrochemical CO2 reduction (CO2R) to CH4 offers a direct pathway to decarbonize natural gas, but practical applications require high current densities, selectivity, and energy efficiency [1,2]. In this study, we present a novel approach to enhance CH4 production via CO2R in aqueous bicarbonate systems [3]. Our research addresses the limitations of previous systems and introduces a paradigm shift in CO2 electroreduction. We leverage the benefits of large-pore Cu electrodes, which facilitate the transport of dissolved CO2 and promote efficient bicarbonate conversion into CO2. This architectural innovation results in high local CO2 concentrations crucial for CH4 selectivity. Furthermore, we introduce an in-situ Cu activation strategy achieved through alternating current operation. This activation method not only generates, but also maintains a highly selective Cu catalyst surface, favoring CH4 production over hydrogen evolution. Our aqueous-fed system achieves remarkable CH4 Faradaic efficiencies, exceeding 70% across a wide current density range (100–750 mA cm-2), and maintains stability for at least 12 hours at 500 mA cm-2. Importantly, our system also demonstrates the highest CH4 product concentration, compared to previous CO2-to-CH4 systems. These findings open new avenues for the large-scale production of CH4 via CO2R, with implications for renewable energy storage and the reduction of greenhouse gas emissions. We believe our innovative approach paves the way for practical and sustainable CH4 production from CO2, contributing to the global effort to combat climate change. References:[1] De Luna, P., Hahn, C., Higgins, D., Jaffer, S.A., Jaramillo, T.F., and Sargent, E.H. (2019). What would it take for renewably powered electrosynthesis to displace petrochemical processes? Science (1979) 364.[2] Kibria, M.G., Edwards, J.P., Gabardo, C.M., Dinh, C.T., Seifitokaldani, A., Sinton, D., and Sargent, E.H. (2019). Electrochemical CO2 Reduction into Chemical Feedstocks: From Mechanistic Electrocatalysis Models to System Design. Advanced Materials 31[3] Obasanjo, C.A., Gao, G., Crane, J., Golovanova V., Garcia de Arquer F. P., Dinh C.-T., High-rate and selective conversion of CO2 from aqueous solutions to hydrocarbons. Nat Commun 14, 3176 (2023)© FUNDACIO DE LA COMUNITAT VALENCIANA SCITOnanoGe is a prestigious brand of successful science conferences that are developed along the year in different areas of the world since 2009. 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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".